A system that incorporates teachings of the present disclosure may include, for example, an accessory having a plurality of tactile-sensitive buttons, a plurality of light sources, wherein each light source emits a controllable spectrum of light through a corresponding one of the plurality of tactile-sensitive buttons, and a controller coupled to the plurality of tactile-sensitive buttons, and the plurality of light sources. The controller can be operable to detect tactile contact of each of the plurality of tactile-sensitive buttons, receive status information associated with a video game, and adjust the spectrum of light emitted by at least a portion of the plurality of light sources according to the status information to indicate one or more aspects of the video game. Additional embodiments are disclosed.

Systems and methods are disclosed for training a machine learning model to control an in-game character or other entity in a video game in a manner that aims to imitate how a particular player would control the character or entity. A generic behavior model that is trained without respect to the particular player may be obtained and then customized based on observed gameplay of the particular player. The customization training process may include freezing at least a subset of layers or levels in the generic model, then generating one or more additional layers or levels that are trained using gameplay data for the particular player.

A system, computer-readable storage medium storing at least one program, and a computer-implemented method for generating game configurations are presented. For example, a system may receive a game configuration request message from a client device being operated by a player playing a virtual game. The game configuration request message may be sent, for example, in response to the player initiating a new game of the virtual game. The system may then select a game configuration based at least in part on historical performance data associated with the selected game configuration. The historical performance data may accumulate performance data from a group of players that previously played the virtual game using the selected game configuration. The system then communicates the selected game configuration to the client device. The player may play the virtual game using the selected game configuration as the initial game configuration for the virtual game.

A method for assisting game play. The method includes monitoring game play of the user playing a gaming application, wherein the user has a defined task to accomplish, wherein the task is associated with a task type. The method includes determining a task type proficiency rule for the task type based on results of a plurality of players taking on a plurality of tasks having the task type. The method includes determining a player proficiency score for accomplishing the task based on the task type proficiency rule. The method includes determining a user predictive rate of success in accomplishing the task based on the player proficiency score, the task type proficiency rule, and the task. The method includes determining a recommendation for the user based on the user predictive rate of success.

A game modification engine modifies configuration settings affecting game play and the user experience in computer games after initial publication of the game, based on device level and game play data associated with a user or cohort of users and on machine-learned relationships between input data and a use metric for the game. The modification is selected to improve performance of the game as measured by the use metric. The modification may be tailored for a user cohort. The game modification engine may define the cohort automatically based on correlations discovered in the input data relative to a defined use metric.

In a game tendency analysis system applied to a game in that a plurality of players compete against each other using an aggregate of a plurality of physical game media, and analyzing a tendency related to constitution of the aggregate used in the game, at least a part of the game media included in an aggregate, which is constituted to be used in the game by each player, is identified, an identification result thereof is separately recorded, as constitution example information which indicates a constitution example of the aggregate, in predetermined constitution example data for each of the aggregates, and a frequent-use media group, which is a combination of game media included in the aggregate with a relatively high frequency, is estimated as an element representing at least a part of the tendency, based on the constitution example data.

Disclosed are a gaming method and system using skill succession in a sport game. The gaming method may include performing a promotion scenario in which at least one trainer character participates when a promotion mode for a player character is activated in a sports game, configuring a skill set in the at least one trainer character to be handed over to the player character based on an establishment of a relationship between the player character and the at least one trainer character according to the progress of the promotion scenario, and processing the use of the succeeded skill by the player character in a process of performing a sports game instance in which the player character participates.

An apparatus, method, and medium for controlling a progress of a video game are provided. A user interface element of the video game is displayed on a display screen. The user interface element is displayed with transparency determined during the progress of the video game. An operation to the user interface element displayed on the display screen is received regardless of the transparency. The progress of the video game is controlled in accordance with the operation to the user interface element displayed on the display screen.

An automated video game testing framework and method includes communicatively coupling an application programming interface (API) to an agent in a video game, where the video game includes a plurality of in-game objects that are native to the video game. The agent is managed as an in-game object of the video game. A test script is executed to control the agent, via the API, to induce gameplay and interrogate one or more target objects selected from the plurality of in-game objects native to the video game. Video game data indicating a behavior of the one or more target objects during the gameplay is received. Based on the received video game data, performance of the video game is evaluated.

In various embodiments of the present disclosure, playstyle patterns of players are learned and used to generate virtual representations (bots) of users. Systems and methods are disclosed that use game session data (e.g., metadata) from a plurality of game sessions of a game to learn playstyle patterns of users, based on user inputs of the user in view of variables presented within the game sessions. The game session data is applied to one or more machine learning models to learn playstyle patterns of the user for the game, and associated with a user profile of the user. Profile data representative of the user profile is then used to control or instantiate bots of the users, or of categories of users, according to the learned playstyle patterns.